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Head of Product Intelligence
Posted 1 hour 2 minutes ago by Careerwise
£110,000 Annual
Permanent
Not Specified
Other
Not Specified, United Kingdom
Job Description
Head of Product Intelligence
We're looking for a Head of Product Intelligence to help a leading organisation unlock a deeper understanding of product usage and customer value across its software portfolio. This role will own the data capabilities that link product behaviour to real-world impact and improve business decisions.
You will be responsible for:
- Defining and owning the product intelligence strategy across the product portfolio
- Owning the telemetry platform strategy, including the design and development of an event data pipeline feeding into a data lakehouse
- Setting standards for product instrumentation (event schemas, naming conventions, versioning, and required properties across all products)
- Building data products, including curated datasets, semantic models, and governed metrics used across the organisation
- Defining data structures for usage, engagement, and outcomes to enable a consistent understanding of products across the organisation
- Shaping product analytics and insights capabilities
- Evaluating product analytics tooling against data architecture, governance requirements, and budget constraints
- Overseeing event ingestion, data pipeline engineering, and platform design to ensure product telemetry data is ingested, transformed, and governed within a unified data lakehouse architecture
- Shaping the measurement strategy by defining success criteria and ensuring insights translate into improved product outcomes
- Building analytics dashboards and insight solutions
- Growing the product intelligence team
Required experience and skills:
- Extensive experience in data analytics engineering and enterprise data architecture
- Experience defining and implementing event instrumentation standards, event infrastructure, and product telemetry architecture
- Experience defining product success metrics, measurement frameworks, and data requirements for decision-making
- Hands-on experience with modern data platforms, including Databricks (experience with MLflow, Unity Catalog, or Feature Store is beneficial)
- Strong SQL and Python skills
- Experience working across the full data life cycle, from instrumentation and ingestion through to transformation, modelling, and analysis
- Experience leading and mentoring technical teams
- Broad experience with product analytics and product experience platforms is an advantage
- Experience using machine learning for behavioural and usage data analysis is beneficial
- Experience building and embedding scalable product data products (curated datasets, APIs, and metrics) that enable consistent measurement and inform product decisions across the life cycle
Careerwise
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